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OpenGridMap: An Open Platform for Inferring Power Grids with Crowdsourced Data

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9424))

Abstract

The energy transition requires profound changes to the power grid, both on the transmission and distribution level. The ability to assess the impact of these changes, e.g., the integration of more solar power or electric mobility, requires data and tools that only exist partially today. The goal of this paper is to introduce OpenGridMap, a new project with the goal of creating an open platform for inferring realistic power grids based on actual data. Our vision is to provide a tool to researchers and practitioners that is able to produce realistic input data for simulation studies. OpenGridMap will support the entire process from data collection to formatting grid data for various purposes. We explore innovative ways to capture data and produce power grid approximations, e.g., using smartphone apps, expert classification, existing map APIs, and graph inference algorithms. The latest developments of the project can be found at opengridmap.com.

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Acknowledgement

We would like to thank Klaus Schreiber, Tanuj Ghinaiya, Clotilde Guinard and Shota Bakuraze from TU München for their contributions to the project. We would also like to thank Michael Metzger from Siemens AG for his contributions as advisor to the project. Most importantly, we would like to thank all the countless contributors that have helped crowdsource geographical data. This research was supported by a German Federal Ministry of Education and Research grant (BMBF 01IS12057) and the Alexander von Humboldt Foundation. During the cause of this work, H.A. Jacobsen held affiliations with the University of Toronto, Canada, and the Technische Universität München, Germany.

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Correspondence to José Rivera .

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Rivera, J., Goebel, C., Sardari, D., Jacobsen, HA. (2015). OpenGridMap: An Open Platform for Inferring Power Grids with Crowdsourced Data. In: Gottwalt, S., König, L., Schmeck, H. (eds) Energy Informatics. EI 2015. Lecture Notes in Computer Science(), vol 9424. Springer, Cham. https://doi.org/10.1007/978-3-319-25876-8_15

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  • DOI: https://doi.org/10.1007/978-3-319-25876-8_15

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